Triple
T16834646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western symphony orchestra |
E409241
|
entity |
| Predicate | mayIncludeSection |
P23744
|
FINISHED |
| Object | keyboard section |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: keyboard section | Statement: [Western symphony orchestra, mayIncludeSection, keyboard section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayIncludeSection Context triple: [Western symphony orchestra, mayIncludeSection, keyboard section]
-
A.
mayIncludeFeature
Indicates that one entity is allowed or able to contain, incorporate, or be associated with a particular feature.
-
B.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
C.
hasOptionalSection
chosen
Indicates that an entity includes a section or component that is not mandatory and may or may not be present.
-
D.
hasSectionIn
Indicates that one entity contains or includes another entity as a section or subdivision within it.
-
E.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b31aa44c8190b4f402f1898e6998 |
completed | April 18, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:23 a.m.